Optical Coherence Tomography (OCT) is a technology for performing high-resolution real time optical imaging in situ. OCT herein refers to any of the transverse scanning extensions of one-dimensional optical coherence detection techniques generally derived from optical coherence domain reflectometry (OCDR) or optical frequency domain reflectometry (OFDR). OCT is an optical measurement and imaging technique using low-coherent light from a broadband source or a tunable laser to create interference signals across the tunable wavelength range of the laser to illuminate both a reference path and a sample path. The superposition of backscatter reflection from the sample path and the optical signal from the reference path creates an interference pattern. The interference pattern contains information about the scattering amplitude as well as the location of the scattering sites in the sample. The longitudinal range within the sample is obtained by using time domain or, frequency domain optical coherence techniques. This depth profile is commonly called an “A-scan”. Cross-sectional images are synthesized by laterally scanning the sample beam over a series of adjacent A-scans, 2-D and 3-D image scanning. OCT provides a mechanism for micrometer resolution measurements.
Evaluation of biological materials using OCT was first disclosed in the early 1990's (see U.S. Pat. No. 5,321,501). More recently it has been demonstrated that frequency domain OCT has significant advantages in speed and signal to noise ratio as compared to time domain OCT (Leitgeb, R. A., et al., Optics Express 11:889-894; de Boer, J. F. et al., Optics Letters 28: 2067-2069; Choma, M. A., and M. V. Sarunic, Optics Express 11: 2183-2189). In Spectral Domain OCT (SD-OCT), sometimes also referred to as Frequency Domain OCT (FD-OCT), and also sometimes also referred to as Spectral Radar (Optics letters, Vol. 21, No. 14 (1996) 1087-1089), the measurement is achieved by examining the spectral content of the interference pattern out of the interferometer.
Improvements in imaging displays frequently accompany improvements in data acquisition methods and devices. For example, development of higher resolution imaging devices creates a need or motivation for higher resolution imaging displays; faster 2-D data acquisition increases the need for high speed data transmission and storage and motivates improvements in 3-D display applications; improvements in the signal to noise ratio in acquired data stimulates new uses and displays for that information.
Large medical imaging data sets, such as those acquired during volumetric imaging, present difficulties in displaying relevant information to operators/users. Medical practitioners need to obtain relevant information quickly in a format that can be efficiently processed. A traditional approach to displaying 3-D volumes is multi-planar reconstruction, which simultaneously displays images from different viewing angles. The user then “scrolls” through the volume looking for relevant images. An alternative approach utilizes modern computational power to identify features of interest and present these to the user through volume rendering. Many times, however, an expert user benefits from observing individual slices of the image data directly. However, selection of these images can be time-consuming and there is a need to improve the means for accessing relevant slices. Herein, a volume slice will generally refer to planar data extracted from a volume, while B-scan will refer to a planar section of the volume that was acquired sequentially. In this sense, a B-scan is a slice, while a slice may be a B-scan. However, the terms are often used interchangeably in the literature and the distinction is often not relevant, since a slice could have been a B-scan under an alternative scanning sequence.
Increased longevity within the population increases the likelihood of age related conditions, such as macular degeneration and glaucoma. Loss of vision, whether partial or complete, dramatically affects quality of life. Whether vision loss is due to changes in the anterior, posterior, or interior of the eye, monitoring change can be crucial to modern patient management.
Change analysis is the detection of change in the condition of a patient over time. Change analysis has great potential for improving patient care in areas such as diagnostic monitoring, intervention planning, and progress monitoring. Modern computing and digital imaging make it possible to store and retrieve large quantities of patient imaging data. Taking diagnostic advantage of these large quantities of data requires improvements in access and management of diagnostic combinations of imaging data within an analysis package. For many diseases, there remains an active debate over what should be measured and tracked over time to track and/or predict disease progression.
Glaucoma is a term generally referring to the collection of diseases related to loss of retinal ganglion cell function. Glaucoma is a slowly progressive disease that, unless treated (and sometimes even when treated), can result in blindness. While raised intraocular pressure (IOP) is a symptom within a sub-family of these diseases, one patient's damaging IOP may well be completely tolerated by another patient with no discernable visual affects. (See U.S. Pat. No. 7,084,128, Yerxa, et al., “Method for reducing intraocular pressure”) Glaucoma Progression Analysis (GPA) software developed with Carl Zeiss Meditec by Dr. Anders Heijl represents the current state of Progression Analysis for Glaucoma. This software monitors visual field loss progression by examining the patient's response to visual field stimuli over time.
Macular degeneration describes a disease or family of diseases that are characterized by a progressive loss of central vision. Vision loss is generally associated with abnormalities in the choroid, Bruch's membrane, the neural retina and/or the retinal pigment epithelium. Destruction of a vascular function within the choroid depletes nourishment to retinal layers and damages overall visual function. Since such destruction is, at present, not generally repairable, recognition of the vascular failure frequently comes too late to be of any real value to the patient. Retinitis and retinopathy are retinal degradations that may progress into total loss of vision. Tracking the change (progression or regression) of eye function both prior to and post treatment improves diagnosis and treatment. Tracking changes over time improves the timing of intervention and enables more effective patient management.
In light of the above, there is a need in the art for an efficient method and apparatus designed to provide to the user relevant image displays and analysis of the large data sets associated with volume OCT imaging. There is a need to display the relevant images needed to track changes over time. The present invention meets the need to provide relevant image displays to the user, overcoming past obstacles by improved data presentation.